宁夏工程技术2024，Vol.23Issue(2)：185-192,8.
一种基于生成对抗网络的图像去雾算法
An Image Dehazing Algorithm Based on Generative Adversarial Networks
摘要
Abstract
In view of the issues such as color distortion,loss of texture details and grid artifacts in the images processed by the existing dehazing algorithms,an end-to-end dehazing algorithm based on generative adversarial networks is proposed.In this algorithm,U-Net is introduced into the generator module,which utilizes multi-scale convolution and skip connections to combine the characteristics of different levels.A hybrid dilated convolution module is employed to capture contextual information,expand the receptive field and alleviate the grid artifacts.Moreover,a composite loss function is utilized to constrain the image boundaries,thereby enhancing the fine quality of the dehazed images and effectively addressing the issues encountered by existing dehazing algorithms.Experimental results of the proposed algorithm on the SOTS data set show that both the objective evaluation metrics and the perceptual quality of the dehazed images outperform all the other compared algorithms.Additionally,experiments on the UA-DETARC data set confirm that the images processed by the proposed algorithm can be applied to the object detection tasks in traffic scenes.关键词
图像去雾/生成对抗网络/混合空洞卷积/复合损失函数/目标检测Key words
image dehazing/generative adversarial networks/hybrid dilated convolution/composite loss function/ob-ject detection分类
信息技术与安全科学引用本文复制引用
李博文,刘进锋..一种基于生成对抗网络的图像去雾算法[J].宁夏工程技术,2024,23(2):185-192,8.基金项目
宁夏自然科学基金项目(2021AAC03084) （2021AAC03084）
